SoroushVahidi/scidocs huggingface dataset:
Large eddy simulations of the HyShot II scramjet
(2012)

The present work is part of a broad effort toward predictive simulations of complex flows at high Reynolds numbers. The main objective of the Stanford PSAAP Center (Pre-dictive Science Academic Alliance Program) is to predict the reacting flow in the HyShot II scramjet experiment carried out in the HEG facility of the German Aerospace Agency DLR (cf. Laurence et al. 2011). Specifically, the objective is to predict the best-estimate of the flow, to estimate the uncertainties from a range of sources in this prediction, and, finally , to quantify the margin to engine unstart. Unstart occurs in supersonic internal flows when the flow becomes choked (e.g., due to excessive friction or heat addition), which initiates an unsteady unstart process that eventually leads to subsonic flow throughout. The unstart process involves a propagation of shock waves upstream in the combustor, the speed of which depends strongly on the amount of heat addition. The experiments by Laurence et al. (2011) indicate propagation velocities of 31 m/s at equivalence ratio (ER) of 0.5, 93 m/s at ER=0.7, and above 200 m/s at ER=1.1. For this problem with fixed mass flux of incoming air, the equivalence ratio is proportional to the fuel mass flux. The length of the HyShot combustor is about 300 mm; thus the unstart process takes about 10 ms at ER=0.5. The experiments were carried out in a shock tube with a test time of about 2.5 ms; thus the unstart process is significantly longer than the test time near the unstart boundary. For this reason, it is clear that shock tube experiments can not give a precise unstart bound. An alternative approach is to use a validated large eddy simulation (LES) method to explore and determine the unstart bound. This is the approach taken here, and the motivation of the work described in this brief. The complexity of the flow (turbulence, shocks, mixing, combustion) implies that a careful multi-stage validation plan is needed. Moreover, the available quantitative experimental data for the HyShot case is limited to measurements of pressure (mean and rms) and heat transfer (although these are highly uncertain) along two lines in the combustor. Therefore, validation on the HyShot problem alone is not sufficient. The first step in the validation is to compute a supersonic flat plate boundary layer as a basic check on the LES method and, specifically, the modeling of the friction and heat transfer at …
Context-free Attacks Using Keyboard Acoustic Emanations
(2014)

The emanations of electronic and mechanical devices have raised serious privacy concerns. It proves possible for an attacker to recover the keystrokes by acoustic signal emanations. Most existing malicious applications adopt context-based approaches, which assume that the typed texts are potentially correlated. Those approaches often incur a high cost during the context learning stage, and can be limited by randomly typed contents (e.g., passwords). Also, context correlations can increase the risk of successive false recognition. We present a context-free and geometry-based approach to recover keystrokes. Using off-the-shelf smartphones to record acoustic emanations from keystrokes, this design estimates keystrokes' physical positions based on the Time Difference of Arrival (TDoA) method. We conduct extensive experiments and the results show that more than 72.2\% of keystrokes can be successfully recovered.
Marriage, honesty, and stability
(2005)

Many centralized two-sided markets form a matching between participants by running a stable marriage algorithm. It is a well-known fact that no matching mechanism based on a stable marriage algorithm can guarantee truthfulness as a dominant strategy for participants. However, as we will show in this paper, in a probabilistic setting where the preference lists of one side of the market are composed of only a constant (independent of the the size of the market) number of entries, each drawn from an arbitrary distribution, the number of participants that have more than one stable partner is vanishingly small. This proves (and generalizes) a conjecture of Roth and Peranson [23]. As a corollary of this result, we show that, with high probability, the truthful strategy is the best response for a given player when the other players are truthful. We also analyze equilibria of the deferred acceptance stable marriage game. We show that the game with complete information has an equilibrium in which a (1 - o(1)) fraction of the strategies are truthful in expectation. In the more realistic setting of a game of incomplete information, we will show that the set of truthful strategies form a (1 + o(1))-approximate Bayesian-Nash equilibrium. Our results have implications in many practical settings and were inspired by the work of Roth and Peranson [23] on the National Residency Matching Program.
A personalized recommender system for pervasive social networks
(2017)

The current availability of interconnected portable devices, and the advent of the Web 2.0, raise the problem of supporting anywhere and anytime access to a huge amount of content, generated and shared by mobile users. On the one hand, users tend to be always connected for sharing experiences and conducting their social interactions with friends and acquaintances, through so-called Mobile Social Networks, further improving their social inclusion. On the other hand, the pervasiveness of communication infrastructures spreading data (cellular networks, direct device-to-device contacts, interactions with ambient devices as in the Internet-of-Things) makes compulsory the deployment of solutions able to filter off undesired information and to select what content should be addressed to which users, for both (i) better user experience, and (ii) resource saving of both devices and network. In this work, we propose a novel framework for pervasive social networks, called Pervasive PLIERS (p-PLIERS), able to discover and select, in a highly personalized way, contents of interest for single mobile users. p-PLIERS exploits the recently proposed PLIERS tag-based recommender system [2] as context a reasoning tool able to adapt recommendations to heterogeneous interest profiles of different users. p-PLIERS effectively operates also when limited knowledge about the network is maintained. It is implemented in a completely decentralized environment, in which new contents are continuously generated and diffused through the network, and it relies only on the exchange of single nodes’ knowledge during proximity contacts and through device-to-device communications. We evaluated p-PLIERS by simulating its behavior in three different scenarios: a big event (Expo 2015), a conference venue (ACM KDD’15), and a working day in the city of Helsinki. For each scenario, we used real or synthetic mobility traces and we extracted real datasets from Twitter interactions to characterize the generation and sharing of user contents.
Recent Advancements in Retinal Vessel Segmentation
(2017)

Retinal vessel segmentation is a key step towards the accurate visualization, diagnosis, early treatment and surgery planning of ocular diseases. For the last two decades, a tremendous amount of research has been dedicated in developing automated methods for segmentation of blood vessels from retinal fundus images. Despite the fact, segmentation of retinal vessels still remains a challenging task due to the presence of abnormalities, varying size and shape of the vessels, non-uniform illumination and anatomical variability between subjects. In this paper, we carry out a systematic review of the most recent advancements in retinal vessel segmentation methods published in last five years. The objectives of this study are as follows: first, we discuss the most crucial preprocessing steps that are involved in accurate segmentation of vessels. Second, we review most recent state-of-the-art retinal vessel segmentation techniques which are classified into different categories based on their main principle. Third, we quantitatively analyse these methods in terms of its sensitivity, specificity, accuracy, area under the curve and discuss newly introduced performance metrics in current literature. Fourth, we discuss the advantages and limitations of the existing segmentation techniques. Finally, we provide an insight into active problems and possible future directions towards building successful computer-aided diagnostic system.
Deep Learning with Low Precision by Half-Wave Gaussian Quantization
(2017)

The problem of quantizing the activations of a deep neural network is considered. An examination of the popular binary quantization approach shows that this consists of approximating a classical non-linearity, the hyperbolic tangent, by two functions: a piecewise constant sign function, which is used in feedforward network computations, and a piecewise linear hard tanh function, used in the backpropagation step during network learning. The problem of approximating the widely used ReLU non-linearity is then considered. An half-wave Gaussian quantizer (HWGQ) is proposed for forward approximation and shown to have efficient implementation, by exploiting the statistics of of network activations and batch normalization operations. To overcome the problem of gradient mismatch, due to the use of different forward and backward approximations, several piece-wise backward approximators are then investigated. The implementation of the resulting quantized network, denoted as HWGQ-Net, is shown to achieve much closer performance to full precision networks, such as AlexNet, ResNet, GoogLeNet and VGG-Net, than previously available low-precision networks, with 1-bit binary weights and 2-bit quantized activations.
Resource Allocation Optimization for Device-to-Device Communication Underlaying Cellular Networks
(2011)

Device-to-Device (D2D) communication will become an important technology in future networks with the increase of the requirements of local communication services. The interference between cellular communication and D2D communication can be coordinated by proper power control and resource allocation. In this paper, we analyze the resource allocation methods for D2D communication underlaying cellular networks. A novel resource allocation method that D2D can reuse the resources of more than one cellular user is proposed. After that, we discuss the selection of the optimal resource allocation method from the proposed method and the conventional methods. Finally, the performance of different methods is evaluated through numerical simulation. The simulation results show that the proposed method is the optimal resource allocation method when the D2D pair locates at the most part of the cell area in both uplink and downlink. The proposed method can improve the sum throughput of cellular communication and D2D communication significantly.
Eleos: ExitLess OS Services for SGX Enclaves
(2017)

Intel Software Guard extensions (SGX) enable secure and trusted execution of user code in an isolated enclave to protect against a powerful adversary. Unfortunately, running I/O-intensive, memory-demanding server applications in enclaves leads to significant performance degradation. Such applications put a substantial load on the in-enclave system call and secure paging mechanisms, which turn out to be the main reason for the application slowdown. In addition to the high direct cost of thousands-of-cycles long SGX management instructions, these mechanisms incur the high indirect cost of enclave exits due to associated TLB flushes and processor state pollution.
 We tackle these performance issues in Eleos by enabling exit-less system calls and exit-less paging in enclaves. Eleos introduces a novel Secure User-managed Virtual Memory (SUVM) abstraction that implements application-level paging inside the enclave. SUVM eliminates the overheads of enclave exits due to paging, and enables new optimizations such as sub-page granularity of accesses.
 We thoroughly evaluate Eleos on a range of microbenchmarks and two real server applications, achieving notable system performance gains. memcached and a face verification server running in-enclave with Eleos, achieves up to 2.2× and 2.3× higher throughput respectively while working on datasets up to 5× larger than the enclave's secure physical memory.
When sex is more than just sex: attachment orientations, sexual experience, and relationship quality.
(2006)

The authors explored the contribution of individual differences in attachment orientations to the experience of sexual intercourse and its association with relationship quality. In Study 1, 500 participants completed self-report scales of attachment orientations and sexual experience. The findings indicated that whereas attachment anxiety was associated with an ambivalent construal of sexual experience, attachment avoidance was associated with more aversive sexual feelings and cognitions. In Study 2, 41 couples reported on their attachment orientations and provided daily diary measures of sexual experiences and relationship interactions for a period of 42 days. Results showed that attachment anxiety amplified the effects of positive and negative sexual experiences on relationship interactions. In contrast, attachment avoidance inhibited the positive relational effect of having sex and the detrimental relational effects of negative sexual interactions. The authors discuss the possibility that attachment orientations are associated with different sex-related strategies and goals within romantic relationships.
Hierarchical graph indexing
(2003)

Traffic analysis, in the context of Telecommunications or Internet and Web data, is crucial for large network operations. Data in such networks is often provided as large graphs with hundreds of millions of vertices and edges. We propose efficient techniques for managing such graphs at the storage level in order to facilitate its processing at the interface level(visualization). The methods are based on a hierarchical decomposition of the graph edge set that is inherited from a hierarchical decomposition of the vertex set. Real time navigation is provided by an efficient two level indexing schema called the gkd*-tree. The first level is a variation of a kd-tree index that partitions the edge set in a way that conforms to the hierarchical decomposition and the data distribution (the gkd-tree). The second level is a redundant R-tree that indexes the leaf pages of the gkd-tree. We provide computational results that illustrate the superiority of the gkd-tree against conventional indexes like the kd-tree and the R*-tree both in creation as well as query response times.
Detection of copy-move image forgery based on discrete cosine transform
(2016)

Since powerful editing software is easily accessible, manipulation on images is expedient and easy without leaving any noticeable evidences. Hence, it turns out to be a challenging chore to authenticate the genuineness of images as it is impossible for human’s naked eye to distinguish between the tampered image and actual image. Among the most common methods extensively used to copy and paste regions within the same image in tampering image is the copy-move method. Discrete Cosine Transform (DCT) has the ability to detect tampered regions accurately. Nevertheless, in terms of precision (FP) and recall (FN), the block size of overlapping block influenced the performance. In this paper, the researchers implemented the copy-move image forgery detection using DCT coefficient. Firstly, by using the standard image conversion technique, RGB image is transformed into grayscale image. Consequently, grayscale image is segregated into overlying blocks of m × m pixels, m = 4.8. 2D DCT coefficients are calculated and reposition into a feature vector using zig-zag scanning in every block. Eventually, lexicographic sort is used to sort the feature vectors. Finally, the duplicated block is located by the Euclidean Distance. In order to gauge the performance of the copy-move detection techniques with various block sizes with respect to accuracy and storage, threshold D_similar = 0.1 and distance threshold (N)_d = 100 are used to implement the 10 input images in order. Consequently, 4 × 4 overlying block size had high false positive thus decreased the accuracy of forged detection in terms of accuracy. However, 8 × 8 overlying block accomplished more accurately for forged detection in terms of precision and recall as compared to 4 × 4 overlying block. In a nutshell, the result of the accuracy performance of different overlying block size are influenced by the diverse size of forged area, distance between two forged areas and threshold value used for the research.
Analysis and validation of proteomic data generated by tandem mass spectrometry
(2007)

The analysis of the large amount of data generated in mass spectrometry–based proteomics experiments represents a significant challenge and is currently a bottleneck in many proteomics projects. In this review we discuss critical issues related to data processing and analysis in proteomics and describe available methods and tools. We place special emphasis on the elaboration of results that are supported by sound statistical arguments.
A three-level, T-type, power electronics building block using Si-SiC hybrid switch for high-speed drives
(2018)

This paper presents the design and implementation of a 100 kW three-level T-type (3L-T2), single-phase power electronics building block (PEBB). The PEBB features switching power devices with associated gate drivers, DC-link capacitors and interconnection busbar. A hybrid switch (HyS), which includes a Si IGBT and a SiC MOSFET in parallel, forms the switching power device in the PEBB. An low-inductive multi-layer laminated busbar was designed to have symmetrical current commutation loops. A major contribution is that this is achieved while no three-level T-type power module was used. A loop inductance of 29 nH was achieved which is lower than the existing state-of-the-art three-level designs in literature. The fabricated prototype PEBB achieves a specific power density of 27.7 kW/kg and a volumetric power density of 308.61 W/in3. Single-phase operation of the PEBB has been demonstrated at the switching frequency of 28 kHz.
Trends in camera based Automotive Driver Assistance Systems (ADAS)
(2014)

Advance Driver Assistance Systems (ADAS), once limited to high end luxury automobiles are fast becoming popular with Mid and entry level segments driven in part by legislation coming in to effect in the latter part of this decade. These systems require support for a wide variety of applications, from surround-view visual systems to safety critical vision applications (eg Pedestrian Detect, automatic braking etc). In this white paper we describe some of the existing and emerging trends and applications in each of these segments along with the requirements and motivations for each of these features. We also highlight TI's automotive class TDA2x device, a state of the art automotive grade device capable of handling complex ADAS applications within a low power and cost budget.
Modeling and control active suspension system for a full car model
(2009)

The purpose of this paper is to investigate the performance of a full car model active suspension system using LQR controller. Dynamic model used in this study is a linear model. A linear model can capture basic performances of vehicle suspension such as body displacement, body acceleration, wheel displacement, wheel deflection, suspension travels, pitch and yawn. Performance of suspension system is determined by the ride comfort and vehicle handling. It can be measured by car body displacement and wheel displacement performance. Two types of road profiles are used as input for the system. Simulation is based on the mathematical model by using MATLAB/SIMULINK software. Results show that the performance of body displacement and wheel displacement can be improved by using Linear Quadratic Regulator control (LQR).
Asymmetric division of labor in human skilled bimanual action: the kinematic chain as a model.
(1987)

This article presents a tentative theoretical framework for the study of asymmetry in the context of human bimanual action. It is emphasized that in man most skilled manual activities involve two hands playing different roles, a fact that has been often overlooked in the experimental study of human manual lateralization. As an alternative to the current concepts of manual preference and manual superiority-whose relevance is limited to the particular case of unimanual actions-the more general concept of lateral preference is proposed to denote preference for one of the two possible ways of assigning two roles to two hands. A simple model describing man's favored intermanual division of labor in the model are the following. 1) The two hands represent two motors, that is, decomplexity is ignored in the suggested approach. 2) In man, the two manual motors cooperate with one another as if they were assembled in series, thereby forming a kinematic chain: In a right-hander allowed to follow his or her lateral preferences, motion produced by the right hand tends to articulate with motion produced by the left. It is suggested that the kinematic chain model may help in understanding the adaptive advantage of human manual specialization.
CONDENSATION—Conditional Density Propagation for Visual Tracking
(1998)

The problem of tracking curves in dense visual clutter is challenging. Kalman filtering is inadequate because it is based on Gaussian densities which, being unimo dal, cannot represent simultaneous alternative hypotheses. The Condensation algorithm uses “factored sampling”, previously applied to the interpretation of static images, in which the probability distribution of possible interpretations is represented by a randomly generated set. Condensation uses learned dynamical models, together with visual observations, to propagate the random set over time. The result is highly robust tracking of agile motion. Notwithstanding the use of stochastic methods, the algorithm runs in near real-time.